You're reading from Azure Data Engineer Associate Certification Guide A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam

Product type Paperback

Published in Feb 2022

Publisher Packt

ISBN-13 9781801816069

Length 574 pages

Edition 1st Edition

Tools

Azure

Concepts

Big Data

Author (1):

Newton Alex

View More author details

Table of Contents (23) Chapters

Preface

1. Part 1: Azure Basics

2. Chapter 1: Introducing Azure Basics FREE CHAPTER

3. Part 2: Data Storage

4. Chapter 2: Designing a Data Storage Structure

5. Chapter 3: Designing a Partition Strategy

6. Chapter 4: Designing the Serving Layer

7. Chapter 5: Implementing Physical Data Storage Structures

8. Chapter 6: Implementing Logical Data Structures

9. Chapter 7: Implementing the Serving Layer

10. Part 3: Design and Develop Data Processing (25-30%)

11. Chapter 8: Ingesting and Transforming Data

12. Chapter 9: Designing and Developing a Batch Processing Solution

13. Chapter 10: Designing and Developing a Stream Processing Solution

14. Chapter 11: Managing Batches and Pipelines

15. Part 4: Design and Implement Data Security (10-15%)

16. Chapter 12: Designing Security for Data Policies and Standards

17. Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)

18. Chapter 13: Monitoring Data Storage and Data Processing

19. Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing

20. Part 6: Practice Exercises

21. Chapter 15: Sample Questions with Solutions

22. Other Books You May Enjoy

Chapter 9: Designing and Developing a Batch Processing Solution

Welcome to the next chapter in the data transformation series. If you have come this far, then you are really serious about the certification. Good job! You have already crossed the halfway mark, with only a few more chapters to go.

In the previous chapter, we learned about a lot of technologies, such as Spark, Azure Data Factory (ADF), and Synapse SQL. We will continue the streak here and learn about a few more batch processing related technologies. We will learn how to build end-to-end batch pipelines, how to use Spark Notebooks in data pipelines, how to use technologies like PolyBase to speed up data copy, and more. We will also learn techniques to handle late-arriving data, scaling clusters, debugging pipeline issues, and handling security and compliance of pipelines. After completing this chapter, you should be able to design and implement ADF-based end-to-end batch pipelines using technologies such as Synapse...